No Effect of Menstrual Phase on Appetite-Regulatory Parameters After a Moderate-Intensity Exercise Session
Bibliographic record
Abstract
INTRODUCTION: Exercise interventions are less effective in generating weight loss in females compared with males suggesting that the menstrual cycle may be important. Fluctuations in ovarian hormones are proposed to alter the appetite-regulatory response to exercise across the menstrual cycle and no study has assessed the response in all distinct hormonal phases. PURPOSE: To compare postexercise appetite-regulating parameters after a single bout of moderate-intensity continuous training (MICT) across three distinct menstrual phases. METHODS: Thirteen females (24 ± 4 y; 24.8 ± 5.4 kg·m -2 ) completed 30 min of MICT running in the follicular phase (FP), ovulatory phase (OP), and luteal phase (LP). Acylated ghrelin, active glucagon-like peptide-1 (GLP-1), plasma glucose, insulin, blood lactate, and appetite perceptions were measured preexercise, 0, 30, 60, and 120 min postexercise. Energy intake was recorded for a 3-d period (day before, of, and after each session). RESULTS: Acylated ghrelin was not different across phases ( P = 0.672, η p2 = 0.032) and only showed a main effect of time ( P = 0.006, η p2 = 0.757) increasing with time. Active GLP-1 was not different across phases ( P = 0.735, η p2 = 0.025) and had a main effect of time ( P < 0.001, η p2 = 0.569) decreasing with time. Appetite perceptions were not different across phases ( P = 0.577, η p2 = 0.045) and exhibited a main effect of time ( P < 0.001, η p2 = 0.786) increasing with time. There was no effect of phase for energy intake ( P = 0.544, η p2 = 0.065). Finally, there were no differences in plasma glucose, insulin, or blood lactate across phases ( P > 0.421, η p2 < 0.070). CONCLUSIONS: There were no divergent appetite responses after MICT running across three hormonally distinct phases (mid-FP, OP, mid-LP) of the menstrual cycle in young eumenorrheic females not using oral contraceptives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".